A Rare Nasopharyngeal Foreign Body

Nasopharynx is an exceptionally rare anatomical location for foreign body impaction. We present a rare case of nasopharyngeal foreign body (NFB) in a 7 years old child. The diagnosis was confirmed by nasal endoscopy. Immediate removal of foreign body (FB) in the nasopharynx was performed under general anesthesia. This rare situation is potentially dangerous, since its dislodgment may cause fatal airway obstruction. Therefore, in all cases with missing foreign bodies in the aerodigestive system, nasopharyngeal impaction should be kept in mind and endoscopic examination of the region should be considere

Simultaneous immunization with Omp25 and L7/L12 provides protection against brucellosis in mice

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Primary Non-Hodgkin's Malignant Lymphoma of the Sinonasal Tract

Primary non-Hodgkin’s lymphomas (NHL) of the sinonasal tract are rather uncommon entities. Morphologically and radiographically, sinonasal lymphomas are difficult to distinguish from other malignant neoplasms or non- neoplastic processes. They have a variable presentation from fulminant destructive manifestations to chronic indolent type of disease and may mimic as carcinomas and invasive fungal infection respectively. We report a case of primary NHL involving sinonasal tract in elderly female, which was clinically and radiologically mimicking as sinonasal malignany and was proven as NHL on histological examination and confirmed by immunohistochemistry. A high index of suspicion, appropriate histopathological examination and immunohistochemistry is necessary to differentiate sinonasal lymphomas from other possibilities. Failure to do so may miss the diagnosis and delay appropriate treatmen

Adaptive Grey Wolf Optimization Technique for Stock Index Price Prediction on Recurring Neural Network Variants

In this paper, we propose a Long short-term memory (LSTM) and Adaptive Grey Wolf Optimization (GWO)--based hybrid model for predicting the stock prices of the Major Indian stock indices, i.e., Sensex. The LSTM is an advanced neural network that handles uncertain, nonlinear, and sequential data. The challenges are its weight and bias optimization. The classical backpropagation has issues of dangling on local minima or overfitting the dataset. Thus, we propose a GWO-based hybrid approach to evolve the weights and biases of the LSTM and the dense layers. We have made the GWO more robust by introducing an approach to improve the best possible solution by using the optimal ranking of the wolves. The proposed model combines the GWO with Adam Optimizer to train the LSTM. Apart from the LSTM, we have also implemented the Adaptive GWO on other variants of Recurring Neural Networks (RNN) like LSTM, Bi-Directional LSTM, Gated Recurrent Units (GRU), and Bi-Directional GRU and computed the corresponding results. The Adaptive GWO here evolves the initial weights and biases of the above-discussed neural networks. In this research, we have also compared the forecasting efficiency of our proposed work with a particle-warm optimization (PSO) based hybrid LSTM model, simple Grey-wolf Optimization (GWO), and Adaptive PSO. According to the experimental findings, the suggested model has effectively used the best initial weights, and its results are the best overall

Hydrodynamic and Advection-Dispersion Simulation of Cool Seawater Discharges from an LNG Facility

7-14The impact of cool seawater discharge in the coastal waters from a Liquefied Natural Gas (LNG) plant has been simulated using MIKE21. In this work, hydrodynamics conditions of the coastal waters were calibrated and corroborated to predict the cool seawater discharge under two plant design scenarios by selecting flow rate 15 m3/s and 10 m3/s with a temperature drop of 5 °C and 7 °C, respectively. The simulations were carried out under different scenarios, to arrive at the best possible case to minimize the potential impact on the coastal environment. Both the simulated scenarios complied with the available World Bank guidelines for LNG facilities. However, the designed scenario of flow rate 10 m3/s with a temperature drop of 7 °C between inlet and outlet presents a better choice as it reduces the pumping power of seawater intake. As there are no Indian guidelines for cool seawater discharges from LNG plant, the present work can support the policymakers and regulators to formulate coherent discharge standards

Exploratory Study for the Development of Road Safety Index on Indian Roads

Road Safety has always been a factor of great concern in India as well as across the world. Road Traffic Accidents have been consistently increasing, and to address this issue, the world's governments declared 2021 to 2030 as the 'Decade of Action' for Road Safety. This rise in accidents can be attributed to the increasing motorization escalation, increasing individual modes of transport, soaring speeds, drinking and driving, increasing transportation network patterns and inefficient enforcement, to name a few. If compendiously scrutinized, the losses due to road traffic incidences are wholly avoidable. A comprehensive study was thus conducted to identify the key aspects which can be attributed to road safety. The six key factors were identified, namely the design of roads, the design of vehicles, the role of the law enforcement agency, the part of the Indian judicial system, the function of the Indian medical system, and general public awareness for developing road safety index. Primary data collection among various population segments identified the relative importance of these factors. The weightage based on the importance of these factors was computed using the Logarithmic Goal Programming Model, and thus, the Road Safety Index was developed

Source Apportionment of PM10 by Positive Matrix Factorization in Urban Area of Mumbai, India

Particulate Matter (PM10) has been one of the main air pollutants exceeding the ambient standards in most of the major cities in India. During last few years, receptor models such as Chemical Mass Balance, Positive Matrix Factorization (PMF), PCA–APCS and UNMIX have been used to provide solutions to the source identification and contributions which are accepted for developing effective and efficient air quality management plans. Each site poses different complexities while resolving PM10 contributions. This paper reports the variability of four sites within Mumbai city using PMF. Industrial area of Mahul showed sources such as residual oil combustion and paved road dust (27%), traffic (20%), coal fired boiler (17%), nitrate (15%). Residential area of Khar showed sources such as residual oil combustion and construction (25%), motor vehicles (23%), marine aerosol and nitrate (19%), paved road dust (18%) compared to construction and natural dust (27%), motor vehicles and smelting work (25%), nitrate (16%) and biomass burning and paved road dust (15%) in Dharavi, a low income slum residential area. The major contributors of PM10 at Colaba were marine aerosol, wood burning and ammonium sulphate (24%), motor vehicles and smelting work (22%), Natural soil (19%), nitrate and oil burning (18%)